Table of Contents
Which AI workload helps smart devices answer stock price questions?
Get a definitive answer for your AI-900 exam on why a smart device answering a stock price question is a clear example of a natural language processing (NLP) workload. Learn how NLP interprets the user’s query and why other AI workloads like knowledge mining are incorrect in this context.
Question
A smart device that responds to the question “What is the stock price of Tailspin Toys?” is an example of which AI workload?
A. Anomaly detection
B. Knowledge mining
C. Computer vision
D. Natural language processing
Answer
D. Natural language processing
Explanation
The correct AI workload is D. Natural language processing. This is because the core task involves the smart device understanding and interpreting a question asked in human language.
The Role of Natural Language Processing
For a smart device to respond to the question, “What is the stock price of Tailspin Toys?”, it must first make sense of the user’s words. This is the primary function of natural language processing. The process involves several key steps:
- Speech-to-Text Conversion: If the question is spoken, the device first converts the audio into text.
- Intent Recognition: The NLP model then determines the user’s goal or “intent.” In this case, the intent is to retrieve a stock price (GetStockPrice).
- Entity Extraction: The model identifies the crucial pieces of information, or “entities,” within the request. Here, the key entity is the company name, “Tailspin Toys.”
After using NLP to understand exactly what the user is asking, the device can then query a financial data service to get the stock price and formulate a response. The initial, critical step of understanding the question is purely an NLP workload.
Why Other Options Are Incorrect
A. Anomaly detection: This workload is used for identifying unusual patterns or outliers in data, such as detecting fraudulent transactions. It is not used for interpreting conversational queries.
B. Knowledge mining: This workload involves ingesting and indexing large volumes of unstructured data (like documents or web pages) to make them searchable. While the stock data might reside in a large database, the act of understanding the user’s question to query that database is an NLP task.
C. Computer vision: This AI workload is focused on analyzing and interpreting visual information from images and videos. It has no role in processing a text- or voice-based question.
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